Algorithmic pricing & collusion; the limits of antitrust enforcement
The combination of big data, large storage capacity and computational power has strengthened the emergence of algorithms in making myriads of business decision. It allows business to gain a competitive advantage by making automatic and optimize decision making. In particular, the use of pricing algorithms allows business to match the demand and supply equilibrium by monitoring & setting dynamic pricing. It benefits consumer alike to see and act on fast changing prices. However, on the downside, the widespread use of algorithm in an industry has the effect of altering the structural characteristic of market such as price transparency, high speed trading which increases the likelihood of collusion. The ability of pricing algorithm to solve the cartel incentive problem by quickly detecting and punishing the deviant further strengthen the enforcement of price fixing agreement. In addition, the use of more advance forms of algorithm such as self-learning algorithm allows business to achieve a tacitly collusive outcome in limited market characteristic even without communication between humans. This raises the fundamental challenge for anti-cartel enforcement as the current law in most jurisdictions is ill-equipped to deal with algorithmic facilitated tacit collusion. The legality of tacit collusion is questionable primarily because the pricing algorithm has the ability to alter the market characteristics where the tacitly collusive outcome is difficult to achieve; thus widening the scope of the so-called ‘oligopoly problem’. This paper studies the usages of pricing algorithms by business in online markets. In particular, the paper identify the conditions under which the algorithm prices causes the harm to consumers. It seeks to analyze how algorithms might facilitate or even causes the collusive outcome without human interventions. Further, it looks at the legal challenges faced by the competition authorities around the globe to deal with the algorithmic let collusion and examine the various approaches suggested to counter act it.
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